diff --git a/egs/librispeech/ASR/transducer/decoder.py b/egs/librispeech/ASR/transducer/decoder.py
index 7b529ac19..333fff300 100644
--- a/egs/librispeech/ASR/transducer/decoder.py
+++ b/egs/librispeech/ASR/transducer/decoder.py
@@ -89,9 +89,9 @@ class Decoder(nn.Module):
             - (h, c), containing the state information for LSTM layers.
               Both are of shape (num_layers, N, C)
         """
-        embeding_out = self.embedding(y)
-        embeding_out = self.embedding_dropout(embeding_out)
-        rnn_out, (h, c) = self.rnn(embeding_out, states)
+        embedding_out = self.embedding(y)
+        embedding_out = self.embedding_dropout(embedding_out)
+        rnn_out, (h, c) = self.rnn(embedding_out, states)
         out = self.output_linear(rnn_out)
 
         return out, (h, c)
diff --git a/egs/librispeech/ASR/transducer_lstm/decoder.py b/egs/librispeech/ASR/transducer_lstm/decoder.py
index 2f6bf4c07..4d531bde1 100644
--- a/egs/librispeech/ASR/transducer_lstm/decoder.py
+++ b/egs/librispeech/ASR/transducer_lstm/decoder.py
@@ -93,9 +93,9 @@ class Decoder(nn.Module):
             - (h, c), containing the state information for LSTM layers.
               Both are of shape (num_layers, N, C)
         """
-        embeding_out = self.embedding(y)
-        embeding_out = self.embedding_dropout(embeding_out)
-        rnn_out, (h, c) = self.rnn(embeding_out, states)
+        embedding_out = self.embedding(y)
+        embedding_out = self.embedding_dropout(embedding_out)
+        rnn_out, (h, c) = self.rnn(embedding_out, states)
         out = self.output_linear(rnn_out)
 
         return out, (h, c)
diff --git a/egs/yesno/ASR/transducer/decoder.py b/egs/yesno/ASR/transducer/decoder.py
index aa8a16845..7ae540d03 100644
--- a/egs/yesno/ASR/transducer/decoder.py
+++ b/egs/yesno/ASR/transducer/decoder.py
@@ -84,9 +84,9 @@ class Decoder(nn.Module):
             - (h, c), which contain the state information for RNN layers.
               Both are of shape (num_layers, N, C)
         """
-        embeding_out = self.embedding(y)
-        embeding_out = self.embedding_dropout(embeding_out)
-        rnn_out, (h, c) = self.rnn(embeding_out, states)
+        embedding_out = self.embedding(y)
+        embedding_out = self.embedding_dropout(embedding_out)
+        rnn_out, (h, c) = self.rnn(embedding_out, states)
         out = self.output_linear(rnn_out)
 
         return out, (h, c)